With the increased number of devices that connect to other devices hosted by commercial or corporate enterprises, it has been noted that there has been a steep increase in the network traffic and data that these connecting devices generate, or that can be generated in regard to these connecting devices. Many corporate or commercial enterprises or business entities capture and/or store such business, corporate, or commercial enterprise specific data for extended periods of time with the ultimate intent of beneficially extracting intelligence in regard to the various connecting devices, servers, services, workstations, and business entities, and their respective activities with respect to devices maintained or operated by the corporate enterprise for future commercial gain.
Further, most, if not all, business and/or commercial enterprises can want to perform data analysis, especially in cases where security incidents occur, or to undertake forensic investigations in situations where devices operated by the corporate entity/enterprise come under attack to temporarily or indefinitely interrupt or suspend services hosted by the server devices controlled/maintained by the enterprise and connected to the Internet (e.g., distributed denial-of-service (DDoS) attack). Many of the enterprises/business capturing and collecting such proprietary data typically do not possess the personnel, infrastructure, facilities, functionalities and/or capabilities, and/or knowledge to efficiently and effectively analyze such data. These enterprises/corporations, being at a relative commercial and competitive disadvantage, must rely on third-party vendors that specialize in performing such data analysis, to provide long term storage and/or supply the computational power necessary for processing the collected enterprise specific data.
In most cases and to date, business enterprises have generally either upload enterprise specific data to a cloud infrastructure for further processing by reliable third-party vendors, or third-party vendors have requested and gained access to propriety enterprise data from storage devices situated within an internal network maintained by the commercial venture. Such unfettered, and/or possibly uncontrolled, access to internal networks and enterprise propriety raw data can raise and create concerns regarding privacy risks to the enterprise and its commercially sensitive, valuable, and proprietary data. As such, in order to mitigate the privacy and security risks associated with “outsourcing” the processing of commercially sensitive data, many commercial enterprises prefer to obviate the risks by processing enterprise sensitive data in-house, despite the fact that they generally have constrained resources and limited technical knowledge in regard to processing and manipulating enterprise specific raw data in order to extract the maximum benefit of such processing and manipulation, which severely undermines the true value of the collected data and the aim of collecting the data.